Update Manyata_UI.py

Manyata_UI.py

@@ -37,15 +37,15 @@ def pull_messages_from_step(
         yield gr.ChatMessage(role="assistant", content=f"**{step_number}**")
 
         # First yield the thought/reasoning from the LLM
-        if hasattr(step_log, "model_output") and step_log.model_output is not None:
+  #      if hasattr(step_log, "model_output") and step_log.model_output is not None:
             # Clean up the LLM output
-            model_output = step_log.model_output.strip()
+  #          model_output = step_log.model_output.strip()
             # Remove any trailing <end_code> and extra backticks, handling multiple possible formats
-            model_output = re.sub(r"```\s*<end_code>", "```", model_output)  # handles ```<end_code>
-            model_output = re.sub(r"<end_code>\s*```", "```", model_output)  # handles <end_code>```
-            model_output = re.sub(r"```\s*\n\s*<end_code>", "```", model_output)  # handles ```\n<end_code>
-            model_output = model_output.strip()
-            yield gr.ChatMessage(role="assistant", content=model_output)
+  #          model_output = re.sub(r"```\s*<end_code>", "```", model_output)  # handles ```<end_code>
+  #          model_output = re.sub(r"<end_code>\s*```", "```", model_output)  # handles <end_code>```
+  #          model_output = re.sub(r"```\s*\n\s*<end_code>", "```", model_output)  # handles ```\n<end_code>
+  #          model_output = model_output.strip()
+  #          yield gr.ChatMessage(role="assistant", content=model_output)
 
         # For tool calls, create a parent message
         if hasattr(step_log, "tool_calls") and step_log.tool_calls is not None: